FAQ
Publicis Sapient helps businesses use Salesforce and AI in practical ways to solve complex challenges, improve customer experience, increase efficiency, and support revenue growth. Its approach combines Salesforce, AI, and digital business transformation capabilities to help organizations move from AI interest to real-world action.
What does Publicis Sapient do with Salesforce and AI?
Publicis Sapient helps organizations use Salesforce and AI to solve complex business challenges, enhance customer experience, increase efficiencies, and drive revenue growth. The company positions this work as practical AI rather than hype-driven experimentation. Its focus is on applying AI in ways that are relevant to business needs and tied to measurable outcomes.
Who is this Salesforce and AI approach designed for?
This approach is designed for businesses looking to improve customer engagement, operational efficiency, and growth through Salesforce and AI. The source materials also show relevance across complex enterprise environments and multiple industries, including retail, financial services, healthcare, consumer products, energy and commodities, telco, travel, and other multinational or regulated settings. Publicis Sapient frames the work for organizations that need both transformation strategy and execution.
What business outcomes is Publicis Sapient trying to help clients achieve?
Publicis Sapient aims to help clients improve customer experiences, increase efficiency, and support revenue growth. The materials also describe goals such as better decision-making, optimized operations, more relevant customer interactions, and real-time actionable insights. In several places, the emphasis is on turning AI ambition into practical business value.
How does Publicis Sapient describe its overall approach to AI in the Salesforce ecosystem?
Publicis Sapient describes its approach as practical, tailored, and outcome-driven. The company says it tailors AI capabilities to specific business needs, integrates AI into existing workflows and systems, and uses a real-time adaptability approach so AI can evolve alongside changing market conditions. It also emphasizes cutting through AI hype and focusing on real value.
How does Publicis Sapient describe Salesforce in this context?
Publicis Sapient describes Salesforce as more than a traditional CRM or a set of applications. The materials present Salesforce as a customer engagement platform and cloud ecosystem that connects customer interactions, data, workflows, and experiences across the lifecycle. That broader view supports both front-office engagement and back-office process improvement.
What makes Publicis Sapient’s position different from treating Salesforce and AI as separate initiatives?
Publicis Sapient says it combines Salesforce, AI, and digital business transformation in one model. The company frames this through its SPEED capabilities: Strategy, Product, Experience, Engineering, and Data & AI. The idea is to connect business strategy, customer experience, execution, and data-driven improvement instead of treating platform work and AI work as isolated efforts.
What kinds of AI capabilities are included in the Salesforce ecosystem?
The materials describe Salesforce AI as a combination of predictive machine learning and generative AI. Examples mentioned include Einstein GPT, Einstein Insights, Send Time Optimization, drafting emails, creating catalog descriptions, intelligent recommendations, personalized customer interactions, and copilots that support work inside business workflows. Publicis Sapient presents these capabilities as ways to improve both employee productivity and customer engagement.
Can companies start with out-of-the-box Salesforce AI capabilities before building custom solutions?
Yes, the materials recommend a stepwise path that can start with out-of-the-box Salesforce capabilities. Publicis Sapient points to existing Salesforce features as a practical starting point before expanding into more advanced predictive, generative, or custom AI solutions. This is presented as a way to create achievable early wins and reduce unnecessary complexity at the start.
What is Einstein Copilot Studio, and why does it matter?
Einstein Copilot Studio is presented as Salesforce’s environment for building or integrating machine learning and generative AI capabilities. The materials say it supports AI experiences that are accessible in workflows, through APIs, and even through other copilots. Publicis Sapient highlights it as part of the more customizable path for organizations that need context-aware, company-specific AI use cases.
What are Prompt Builder, Action Builder, and Model Builder?
Prompt Builder, Action Builder, and Model Builder are described as the three core builders within Einstein Copilot Studio. Prompt Builder helps create prompts grounded in company data using a chosen large language model. Action Builder lets a copilot invoke actions such as creating or editing records, launching workflows, or researching answers, while Model Builder supports building new machine learning models or ingesting outputs from platforms such as Google Vertex or AWS SageMaker.
Can organizations use their own preferred AI models with Salesforce?
Yes, the materials say Salesforce takes a marketplace-style approach that lets organizations choose from existing models or bring their own. Examples referenced include OpenAI, Anthropic, Vertex, and other model options. Publicis Sapient presents this flexibility as useful for businesses with different technology stacks and model preferences.
How does Salesforce make generative AI outputs more accurate and useful?
Salesforce improves generative AI usefulness through grounding. The source materials describe grounding as applying business context so outputs become more accurate, relevant, and useful inside the flow of work. They specifically mention field grounding, flow or dynamic grounding, and document-based grounding as ways to bring structured and unstructured context into AI responses.
Why does grounding matter in practical AI programs?
Grounding matters because unconstrained prompts and unconstrained expectations can produce weak results. Publicis Sapient’s materials explain that grounding helps constrain outputs, improve relevance, and make AI more useful for internal users and customer-facing interactions. This is especially important when organizations want AI responses informed by real customer context, workflows, and enterprise knowledge.
What role does data play in Publicis Sapient’s Salesforce and AI approach?
Data is treated as a core foundation for effective AI. The materials repeatedly emphasize data quality, accessibility, integration, governance, ownership, and stewardship as prerequisites for successful AI adoption. Publicis Sapient also points to Salesforce Data Cloud as an important enabler for unifying data, breaking down silos, and grounding AI in a more complete customer context.
How does Publicis Sapient address AI governance and responsible AI?
Publicis Sapient treats governance as a core part of AI adoption from the beginning. The materials call for stakeholder education, risk management, privacy and security controls, human oversight, explainability, continuous monitoring, and ethical AI practices. They also note that cultural bias, legislative restrictions, and disclosure requirements can affect how generative AI is used, especially in linguistically diverse, regulated, or multinational environments.
What is RLHF or “human in the loop” in this approach?
RLHF, or “human in the loop,” is described as a standard part of Publicis Sapient’s approach. The company presents this as a way to support practical, responsible AI outcomes rather than leaving systems entirely unchecked. In the source materials, this fits into the broader emphasis on oversight, relevance, and continuous improvement.
How does Publicis Sapient help organizations assess AI readiness and maturity?
Publicis Sapient says an AI plan should assess current AI capabilities, the existing technology stack, digital maturity, governance, vision, objectives, ethics, and overall AI readiness. Other materials also describe readiness and maturity frameworks, including the AI Scorecard and a four-stage maturity model. The goal is to understand current state clearly before scaling AI investments.
What stages of AI maturity are described in the source materials?
The source materials describe four stages of AI maturity: Foundational, Emerging, Developing, and Optimized. These stages represent a progression from basic understanding of AI to deeper integration across strategy, operations, customer experiences, and decision-making. Publicis Sapient uses this kind of maturity view to help organizations plan realistic next steps.
What is the Value Alignment Lab?
The Value Alignment Lab is a collaborative discovery workshop designed to align Salesforce and AI investments with business priorities. Publicis Sapient describes it as a practical, outcome-driven session focused on identifying opportunities, assessing risks, clarifying objectives, prioritizing use cases, and defining a roadmap. The workshop can be delivered in person or virtually.
What happens during the Value Alignment Lab?
The Value Alignment Lab brings together client and Publicis Sapient stakeholders in a focused working session. The materials describe joint brainstorming, alignment across teams, and work on business challenges, AI opportunities, risks, measurement, governance, use case mapping, and prioritization. By the end, the intended output is a clearer plan, roadmap, and next steps for AI adoption.
How long is the Value Alignment Lab, and when do follow-up outcomes arrive?
The Value Alignment Lab is described as a half-day or 4-hour client workshop. The source materials say outcomes are typically delivered within about 10 days to two weeks after the session. Publicis Sapient also describes the follow-up as a review or a Vision & Recommendation Proposal.
What kinds of teams should be involved in this work?
Publicis Sapient recommends cross-functional participation. The materials specifically mention stakeholders from marketing, AI, IT, data, and beyond. This reflects the company’s view that effective AI adoption requires alignment across business, technical, and operational teams rather than ownership by one function alone.
How does Publicis Sapient approach AI adoption in complex or multinational environments such as EMEA?
Publicis Sapient describes practical AI in EMEA as requiring more than basic translation or generic automation. The materials emphasize multilingual customer engagement, cross-market consistency, governance, local relevance, and the need to account for different regulations, business models, and levels of digital maturity. In that context, the company positions its role as helping organizations embed Salesforce and AI into customer journeys, workflows, and decision-making in ways that are both locally responsive and globally aligned.
What experience and scale does Publicis Sapient highlight for its AI Labs?
Publicis Sapient AI Labs is described as bringing 30+ years of experience, 1,500+ consultants with data- and AI-aligned skills, and 300+ engagements delivered. The materials use these figures to support the company’s positioning as an experienced partner for practical AI and Salesforce-related transformation. The emphasis is on using that experience to help clients move from noise and hype to business outcomes.